Methodology
How we source, score, and verify everything.
Fluenta resources are synthesized from 200+ external sources and verified against 25 live data integrations before every publish. This page explains exactly which sources, exactly which checks, and exactly what happens when we get something wrong.
The 200+ sources, by category
We do not list every individual source on this page — the full list is rebuilt weekly and reaches well past 200 entries. Below is the canonical category map. Every claim we publish can be traced to at least one of these.
Search and demand signals
- — DataForSEO ranked keywords + domain intersection (13 competitor domains)
- — Ahrefs keyword difficulty and traffic estimates
- — Google Trends 5-year normalized search velocity
- — Reddit + X + Hacker News + Quora complaint scraping (Fluenta agent pipeline)
Funding and operator data
- — Crunchbase funding rounds and stage filters
- — PitchBook private market comps (where licensed)
- — Public S-1 + 10-K filings for benchmarks
- — First Round, a16z, Sequoia, YC public posts and podcasts
Product and competitor data
- — G2 and Capterra category rankings + verified review counts
- — Stripe Press, Lenny's Newsletter, Reforge published case studies
- — Direct competitor changelog and pricing-page scrapes
- — Job-posting scrapes (Indeed + LinkedIn) as a hiring-intent proxy
Fluenta proprietary data
- — Live Research Snapshot (LRS) — Fluenta's internal scoring engine, refreshed weekly
- — 1,492 scored startup ideas across 41 sectors (refreshed quarterly)
- — Aggregated X-Ray report patterns from real customer runs
- — Founder community boards and curated collections
The 5 verification steps every article passes
1. Source triangulation
Every numerical claim must reconcile across at least two of the source categories above. If only one source supports a number, we mark the claim as 'directional' and never use it as a headline stat.
2. Live data backtest
Before publishing, every report and guide is run against 25 live data integrations. Claims that fail to reproduce are dropped — not softened. We would rather ship a shorter article than a confidently wrong one.
3. Named-author byline
Every long-form article has a human byline (most often Oleg Ivanov, our co-founder). Bylined authors take responsibility for claims and corrections. Pseudonyms and 'Fluenta Editorial' bylines are reserved for aggregated weekly signal reports.
4. Public corrections log
When we find a mistake — ours or a source's — we update the article inline, date-stamp the correction in the footer, and re-issue the LRS for that issue. Past versions remain accessible by Issue number.
5. Quote provenance
Every direct quote includes a permalink to the original post, paper, talk, or interview. Where the source is paywalled, we include the quote, the paywall flag, and a publicly available paraphrase from the same author.
What "LRS" means
- LRS = Live Research Snapshot. It is Fluenta's internal versioning system for weekly research drops.
- Each LRS issue has a number (e.g. Issue 92) and a publish date. Reports tagged with the same LRS share the same source freshness window.
- Every LRS issue is free to read end-to-end. The paid product is the X-Ray report engine: from $7 per run, 20 minutes, your idea scored against the same 25 live data feeds the LRS uses.
Found something wrong?
Email [email protected] with subject "Correction request" plus the article URL and the claim you're disputing. Verified corrections ship within 48 hours and are logged in the article footer.